Reduced-order modeling and control for subsonic cavity flows

E. Caraballo, J. Little, X. Yuan, M. Debiasi, A. Serrani, M. Samimy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

A benchmark problem in active aerodynamic flow control, suppression of pressure oscillations induced by flow over a shallow cavity, is used in this paper to present a comprehensive approach to reduced-order model based flow control. Proper orthogonal decomposition and Galerkin projection techniques are used to obtain a reduced-order model of the flow dynamics from experimental data. The model is made amenable to control design by means of a control separation technique. Quadratic stochastic estimation is used to correlate flow field data with surface pressure measurements to reconstruct the state of the model in real time. Experimental results show that a linear-quadratic controller designed on the basis of the reduced-order model achieves a significant attenuation of the resonant tone with a redistribution of the energy into other frequencies, and exhibits a certain degree of robustness when operating in off-design conditions.

Original languageEnglish (US)
Title of host publicationProceedings of the 45th IEEE Conference on Decision and Control 2006, CDC
Pages4603-4608
Number of pages6
StatePublished - Dec 1 2006
Externally publishedYes
Event45th IEEE Conference on Decision and Control 2006, CDC - San Diego, CA, United States
Duration: Dec 13 2006Dec 15 2006

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0191-2216

Other

Other45th IEEE Conference on Decision and Control 2006, CDC
CountryUnited States
CitySan Diego, CA
Period12/13/0612/15/06

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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  • Cite this

    Caraballo, E., Little, J., Yuan, X., Debiasi, M., Serrani, A., & Samimy, M. (2006). Reduced-order modeling and control for subsonic cavity flows. In Proceedings of the 45th IEEE Conference on Decision and Control 2006, CDC (pp. 4603-4608). [4178143] (Proceedings of the IEEE Conference on Decision and Control).